code: def generate_dict_answers():
      """
      Generates dictionary containing answers that I have pre-calculated for iris dataset.
      """
      global g_iris_setosa_sepal_len
      global g_iris_versicolor_sepal_wid
      global g_iris_virginica_petal_wid
      global g_iris_versicolor_petal_len_NA_ignore
      global g_iris_versicolor_petal_len_NA_rm
  
      # collect pre-calculated information
      g_iris_setosa_sepal_len["mean_sepal_len"] = 5.006
      g_iris_setosa_sepal_len["sum_sepal_len"] = 250.3
      g_iris_setosa_sepal_len["sumSquares_sepal_len"] = 1259.09
      g_iris_setosa_sepal_len["max_sepal_len"] = 5.8
      g_iris_setosa_sepal_len["min_sepal_len"] = 4.3
      g_iris_setosa_sepal_len["var_sepal_len"] = (
          g_iris_setosa_sepal_len["sumSquares_sepal_len"]
          - 2
          * g_iris_setosa_sepal_len["mean_sepal_len"]
          * g_iris_setosa_sepal_len["sum_sepal_len"]
          + 50
          * g_iris_setosa_sepal_len["mean_sepal_len"]
          * g_iris_setosa_sepal_len["mean_sepal_len"]
      ) / 49.0
      g_iris_setosa_sepal_len["sdev_sepal_len"] = math.sqrt(
          g_iris_setosa_sepal_len["var_sepal_len"]
      )
  
      g_iris_versicolor_sepal_wid["mean_sepal_wid"] = 2.77
      g_iris_versicolor_sepal_wid["sum_sepal_wid"] = 138.5
      g_iris_versicolor_sepal_wid["sumSquares_sepal_wid"] = 388.47
      g_iris_versicolor_sepal_wid["max_sepal_wid"] = 3.4
      g_iris_versicolor_sepal_wid["min_sepal_wid"] = 2.0
      g_iris_versicolor_sepal_wid["var_sepal_wid"] = (
          g_iris_versicolor_sepal_wid["sumSquares_sepal_wid"]
          - 2
          * g_iris_versicolor_sepal_wid["mean_sepal_wid"]
          * g_iris_versicolor_sepal_wid["sum_sepal_wid"]
          + 50
          * g_iris_versicolor_sepal_wid["mean_sepal_wid"]
          * g_iris_versicolor_sepal_wid["mean_sepal_wid"]
      ) / 49.0
      g_iris_versicolor_sepal_wid["sdev_sepal_wid"] = math.sqrt(
          g_iris_versicolor_sepal_wid["var_sepal_wid"]
      )
  
      g_iris_virginica_petal_wid["mean_petal_wid"] = 2.026
      g_iris_virginica_petal_wid["sum_petal_wid"] = 101.3
      g_iris_virginica_petal_wid["sumSquares_petal_wid"] = 208.93
      g_iris_virginica_petal_wid["max_petal_wid"] = 2.5
      g_iris_virginica_petal_wid["min_petal_wid"] = 1.4
      g_iris_virginica_petal_wid["var_petal_wid"] = (
          g_iris_virginica_petal_wid["sumSquares_petal_wid"]
          - 2
          * g_iris_virginica_petal_wid["mean_petal_wid"]
          * g_iris_virginica_petal_wid["sum_petal_wid"]
          + 50
          * g_iris_virginica_petal_wid["mean_petal_wid"]
          * g_iris_virginica_petal_wid["mean_petal_wid"]
      ) / 49.0
      g_iris_virginica_petal_wid["sdev_petal_wid"] = math.sqrt(
          g_iris_virginica_petal_wid["var_petal_wid"]
      )
  
      g_iris_versicolor_petal_len_NA_ignore["sum_petal_len"] = 204.5
      g_iris_versicolor_petal_len_NA_ignore[
          "sumSquares_petal_len"
      ] = 881.95
      g_iris_versicolor_petal_len_NA_ignore["mean_petal_len"] = (
          g_iris_versicolor_petal_len_NA_ignore["sum_petal_len"] / 50.0
      )
      g_iris_versicolor_petal_len_NA_ignore["max_petal_len"] = 5.1
      g_iris_versicolor_petal_len_NA_ignore["min_petal_len"] = 3.0
      g_iris_versicolor_petal_len_NA_ignore["var_petal_len"] = (
          g_iris_versicolor_petal_len_NA_ignore["sumSquares_petal_len"]
          - 2
          * g_iris_versicolor_petal_len_NA_ignore["mean_petal_len"]
          * g_iris_versicolor_petal_len_NA_ignore["sum_petal_len"]
          + 50
          * g_iris_versicolor_petal_len_NA_ignore["mean_petal_len"]
          * g_iris_versicolor_petal_len_NA_ignore["mean_petal_len"]
      ) / 49.0
      g_iris_versicolor_petal_len_NA_ignore[
          "sdev_petal_len"
      ] = math.sqrt(
          g_iris_versicolor_petal_len_NA_ignore["var_petal_len"]
      )
  
      g_iris_versicolor_petal_len_NA_rm["sum_petal_len"] = 204.5
      g_iris_versicolor_petal_len_NA_rm["sumSquares_petal_len"] = 881.95
      g_iris_versicolor_petal_len_NA_rm["mean_petal_len"] = (
          g_iris_versicolor_petal_len_NA_rm["sum_petal_len"] / 48.0
      )
      g_iris_versicolor_petal_len_NA_rm["max_petal_len"] = 5.1
      g_iris_versicolor_petal_len_NA_rm["min_petal_len"] = 3.0
      g_iris_versicolor_petal_len_NA_rm["var_petal_len"] = (
          g_iris_versicolor_petal_len_NA_rm["sumSquares_petal_len"]
          - 2
          * g_iris_versicolor_petal_len_NA_rm["mean_petal_len"]
          * g_iris_versicolor_petal_len_NA_rm["sum_petal_len"]
          + 48
          * g_iris_versicolor_petal_len_NA_rm["mean_petal_len"]
          * g_iris_versicolor_petal_len_NA_rm["mean_petal_len"]
      ) / 47.0
      g_iris_versicolor_petal_len_NA_rm["sdev_petal_len"] = math.sqrt(
          g_iris_versicolor_petal_len_NA_rm["var_petal_len"]
      )
  
file_path: h2o-3/h2o-py/tests/testdir_munging/pyunit_groupby_allOps.py
imports: import sys
  import h2o
  import math
  from tests import pyunit_utils
  from h2o.utils.typechecks import assert_is_type
  from h2o.frame import H2OFrame
label_desc: Use image node_id 5 for calling a global function with example usage: generate_dict_answers() without return types